CRS is disabling and is associated with high direct and indirect costs, yet little is known about the epidemiology, etiologic heterogeneity, and individual and societal burden. There is a substantial gap in understanding how to frame research needs for CRS and improve patient outcomes. This project will complete a large-scale epidemiologic study of CRS by leveraging the unique data and population assets of the Geisinger Clinic, including a primary care population of 400,000 patients in over 30 counties in Pennsylvania. We will combine longitudinal self-reported and electronic health record data with new clinical and research measurements to address gaps in understanding. While relatively little is known about the natural history of CRS, it is clear that: many patients in the general population have nasal and sinus symptoms; some of these patients are diagnosed with allergic rhinitis or episodes of ARS (symptoms for 7d to 4wk, to eliminate patients with the common cold); some of these patients progress to CRS with symptoms present for at least 12 weeks; many patients with CRS have episodes of exacerbations, with a prominent worsening of symptoms over the baseline; many patients, especially those seen in tertiary centers, have recalcitrant CRS; and the natural history must include some therapeutic and probably spontaneous remissions. The incidence, prevalence, transition rates, and risk factors for each ofthe steps in the framework are not well known. Since relatively little research exists in population-based samples, it is likely that most studies have focused on patients who have failed therapy, the recalcitrant group. In the proposed research, we will estimate CRS prevalence, incidence, and remission using clinically validated criteria for general population samples that represent the full spectrum of CRS; describe patterns of CRS exacerbation and remission and the factors that explain variability; determine how CRS with and without nasal polyps cases differ from each other; evaluate a variety of community environmental risk factors for CRS using existing geospatial data on key environmental conditions; and estimate the direct and indirect costs of CRS.